| The signals that potential contributors look for when choosing open-source projects HS Qiu, YL Li, S Padala, A Sarma, B Vasilescu Proceedings of the ACM on Human-Computer Interaction 3 (CSCW), 1-29, 2019 | 80 | 2019 |
| A study of Bayesian neural network surrogates for Bayesian optimization YL Li, TGJ Rudner, AG Wilson arXiv preprint arXiv:2305.20028, 2023 | 25 | 2023 |
| Bean machine: A declarative probabilistic programming language for efficient programmable inference N Tehrani, NS Arora, YL Li, KD Shah, D Noursi, M Tingley, N Torabi, ... International Conference on Probabilistic Graphical Models, 485-496, 2020 | 13 | 2020 |
| Pre-tokenization of multi-word expressions in cross-lingual word embeddings N Otani, S Ozaki, X Zhao, Y Li, M St Johns, L Levin Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 8 | 2020 |
| Accelerating metropolis-hastings with lightweight inference compilation F Liang, N Arora, N Tehrani, Y Li, M Tingley, E Meijer International Conference on Artificial Intelligence and Statistics, 181-189, 2021 | 4 | 2021 |
| Newtonian Monte Carlo: single-site MCMC meets second-order gradient methods NS Arora, NK Tehrani, KD Shah, M Tingley, YL Li, N Torabi, D Noursi, ... arXiv preprint arXiv:2001.05567, 2020 | 2 | 2020 |
| Newtonian Monte Carlo: a second-order gradient method for speeding up MCMC NS Arora, NK Tehrani, KD Shah, M Tingley, YL Li, N Torabi, D Noursi, ... Second Symposium on Advances in Approximate Bayesian Inference, 2019 | 2 | 2019 |
| On representation learning under class imbalance R Shwartz-Ziv, M Goldblum, YL Li, CB Bruss, AG Wilson | 1 | 2023 |
| PPL Bench: Evaluation Framework For Probabilistic Programming Languages S Kulkarni, KD Shah, N Arora, X Wang, YL Li, NK Tehrani, M Tingley, ... arXiv preprint arXiv:2010.08886, 2020 | | 2020 |
